Flexible job shop scheduling method of ECM rule distribution estimation algorithm
A distribution estimation algorithm, workshop scheduling technology, applied in control/regulation systems, instruments, comprehensive factory control, etc., can solve the problems of lack of general applicability, efficiency, stability and security of scheduling methods, and achieve strong learning ability and adaptability, enhance the search ability, and speed up the effect of convergence
Active Publication Date: 2020-08-28
无锡市江南橡塑机械有限公司
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Problems solved by technology
Current scheduling methods often lack universal applicability, efficiency, stability and security
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example 1
[0068] Example 1 is a 15×10 calculation example in the Kacem test function, and its processing task information can be found in relevant references.
[0069] Solving Example 1, the evolutionary convergence curves of the three algorithms are as follows image 3 As shown, the Gantt chart of the corresponding scheduling result is as follows Figure 4 shown. Table 1 shows the data of the maximum completion time of Example 1 by the three algorithms.
[0070] Table 1
[0071]
[0072] Depend on image 3 It can be seen that, in contrast, the evolutionary convergence curve of the ECM regular distribution estimation algorithm converges faster and has higher convergence precision.
[0073] As can be seen from Table 1, contrast GA and PSO algorithm, from mean value, minimum value, maximum value, the optimization result of the ECMEDA algorithm that the present invention proposes is all better than GA and PSO algorithm, and the precision of optimization result is higher; From varian...
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The invention provides a flexible job shop scheduling method based on an ECM rule distribution estimation algorithm, and the method employs a process probability matrix and an ECM rule for the processsorting and machine distribution of flexible job shops. According to the scheme, the method comprises the steps of: firstly, obtaining an initial population by adopting a random initialization method; selecting a dominant population through an elitist selection strategy, updating the process probability matrix by adopting the dominant population, generating a new process processing scheme by adopting a new process probability matrix and a roulette method, generating a new machine allocation scheme by adopting an ECM rule, and circulating the strategy until the algorithm is finished. The process probability matrix of the scheme can learn the process allocation rule and has very strong learning ability and adaptability, the ECM rule generates a new machine allocation scheme for the earliestcompletion time, the information of the optimization target is fully utilized, the objectivity is stronger, the search ability of the algorithm is enhanced, and the convergence speed of the algorithmis accelerated.
Description
technical field [0001] The invention relates to the field of distribution estimation algorithms, in particular to a flexible job shop scheduling method for ECM rule distribution estimation algorithms. Background technique [0002] In the manufacturing fields of automobile, assembly, textile manufacturing, chemical materials, semiconductor manufacturing and other manufacturing fields, the problem of flexible job shop scheduling has been widely concerned by academia and industry. When all production constraints are satisfied, production scheduling needs to determine its processing sequence and allocate available production resources. This kind of problem has high flexibility and exponential complexity. [0003] Currently, there are three main categories of solutions to such problems, including exact algorithms, heuristics, and metaheuristics. Early researchers often used the branch and bound method and priority assignment rules to solve the application scenarios of small-scal...
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IPC IPC(8): G05B19/418
CPCG05B19/41885G05B2219/32339
Inventor 黄松章华
Owner 无锡市江南橡塑机械有限公司